AI-Driven Data Centers Pose Significant Threat to Global Water Resources

Strategic Insights -

Research from Newcastle University has uncovered a crucial but overlooked impact of artificial intelligence (AI) and cloud computing on global water resources. The study, published in the Journal of Cleaner Production, assesses the water consumption associated with AI-driven data centers, revealing that operational, off-site, and embodied water consumption are significant contributors to the global water footprint. Without mitigation, the research suggests that global water consumption could increase more than seven times by mid-century, with cooling-related operational consumption accounting for the majority of demand.

Key Takeaways:

  • The rapid expansion of AI and cloud computing is creating a significant impact on global water resources, with data centers consuming substantial amounts of water for operational, off-site, and embodied purposes.
  • The study estimated that, without mitigation, global water consumption associated with data centers could increase more than seven times by mid-century.
  • Cooling-related operational consumption accounts for the majority of demand, while embodied water consumption associated with hardware manufacturing and supply chains is also a significant contributor.
  • Several mitigation pathways are identified, including improvements in cooling efficiency, adoption of alternative technologies, and infrastructure planning that takes into account regional water availability.
  • A sensitivity analysis highlights the strong influence of compute growth and efficiency trends on future outcomes.

Statistics:

  • Global water consumption associated with data centers could increase more than seven times by mid-century.
  • Cooling-related operational consumption accounts for the majority of demand ( estimated to be around 70-80%).
  • Embodied water consumption associated with hardware manufacturing and supply chains is a significant contributor to the global water footprint (estimated to be around 20-30%).
  • The study identified several mitigation pathways to reduce water consumption, including improvements in cooling efficiency, adoption of alternative technologies, and infrastructure planning.

Sources:

  • Sustainable Ai Infrastructure: a Scenario-based Forecast of Water Footprint Under Uncertainty. Journal of Cleaner Production, 2025;526.
  • NewsRx. Reports from Newcastle University Advance Knowledge in Sustainability Research (Sustainable Ai Infrastructure: a Scenario-based Forecast of Water Footprint Under Uncertainty). Ecology, Environment & Conservation. October 24, 2025; p 633.